113 citations · 208 across the 11 of their papers we have counts for
3 papers · 2 filters
Sensitivity Analysis for Predictive Uncertainty in Bayesian Neural Networks
Stefan Depeweg, José Miguel Hernández-Lobato, Steffen Udluft +1
We derive a novel sensitivity analysis of input variables for predictive epistemic and aleatoric uncertainty. We use Bayesian neural networks with latent variables as a model class…
Decomposition of Uncertainty in Bayesian Deep Learning for Efficient and Risk-sensitive Learning
Stefan Depeweg, José Miguel Hernández-Lobato, Finale Doshi-Velez +1
Bayesian neural networks with latent variables are scalable and flexible probabilistic models: They account for uncertainty in the estimation of the network weights and, by making…
Uncertainty Decomposition in Bayesian Neural Networks with Latent Variables
Stefan Depeweg, José Miguel Hernández-Lobato, Finale Doshi-Velez +1
Bayesian neural networks (BNNs) with latent variables are probabilistic models which can automatically identify complex stochastic patterns in the data. We describe and study in th…